Problems

Trust breaks: If stakeholders can't trust the numbers, why would they trust the people behind them?

• Impact to business: Marketing targeted "high-value" customers who weren't actually valuable, while finance unknowingly reported inflated revenue.

• Manual investigation and validation: Tracing the root cause meant hours of manual SQL digging, and the proving the fix was correct required complex custom queries, CSV exports, and Excel spot-checking.

• No clear communication path: Technical SQL fixes don't translate well to business stakeholders who need to understand what changed and why they should trust the new numbers.

Solutions

• Visibility: Make what changed instantly clear
  With breaking change analysis, you can identify that only `customer_segments` would be affected downstream, and use column-level lineage to trace which columns are impacted.

• Verifiability: Prepare evidence and bring stakeholders into the loop
  All findings, queries, and impacts documented in one checklist, making review and approval straightforward for both technical and business teams.

• Velocity: Build repeatable processes for sustainable speed
  With one-click sharing, the interactive UI gives stakeholders the complete story which they can explore themselves. Follow the developer's thought process step-by-step, examine the evidence firsthand, and ask informed questions based on what they discover.